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Imaging Local Ca2+ Signals in Cultured Mammalian Cells
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Calcium Imaging with Super-Resolution Radial Fluctuations.

Yuan-Hao Lee1, Shuo Zhang2,3, Cheryl Kyles Mitchell1

  • 1Department of Ophthalmology and Visual Science, University of Texas Health Science Center at Houston, Houston, USA.

Bioscience and Bioengineering (Boston, Mass.)
|October 2, 2020
PubMed
Summary

Super-resolution radial fluctuations (SRRF) analysis enhances the resolution of calcium signals, improving the detection and spatial accuracy of fluorescent probes for cellular imaging. This method accurately identifies subcellular molecules and validates its merit in calcium live imaging.

Keywords:
Calcium SignalsImage ResolutionSRRF

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Area of Science:

  • Cell Biology
  • Biophysics
  • Microscopy

Background:

  • Calcium signals are crucial secondary messengers regulating numerous physiological functions.
  • Biomarker-targeted fluorescent probes are essential for detecting calcium microdomain signals.
  • Accurate imaging of delicate calcium signals is challenging due to resolution limitations.

Purpose of the Study:

  • To evaluate the Super-Resolution Radial Fluctuations (SRRF) algorithm for enhancing the resolution and accuracy of calcium signal imaging.
  • To compare the spatial and temporal characteristics of fluorescent probes before and after SRRF analysis.
  • To validate the application of SRRF in live calcium imaging using a reporter gene system.

Main Methods:

  • Utilized the SRRF algorithm to analyze fluorescent probe signals in immunofluorescence-stained retina cryostat slices and transfected HeLa cells.
  • Assessed spatial accuracy using immunofluorescence staining of connexin 36 (Cx36) in retina.
  • Characterized temporal dynamics by recording Cx36-GCaMP calcium indicator changes in HeLa cells.
  • Employed Image J and Matlab for image processing and analysis.

Main Results:

  • SRRF reconstruction provided accurate measurements for identifying subcellular molecules like gap junctions.
  • SRRF generated superior image resolution compared to conventional imaging, enabling precise registration of individual signals.
  • Temporal changes in fluorescence intensity between SRRF and non-SRRF images showed significant correlation, even with background subtraction.
  • Quantitative analysis confirmed the correlation of fluorescence intensity changes with or without background subtraction.

Conclusions:

  • SRRF algorithm significantly improves image resolution for precise identification of subcellular structures and signals.
  • The method offers enhanced spatial accuracy for detecting delicate calcium signals.
  • SRRF application is validated as a valuable tool for calcium live imaging, improving the analysis of cellular dynamics.